Coastal Altimetry Using Interferometric Phase From GEO Satellite in Quasi-Zenith Satellite System

He, Yunqiao; Gao, Fan; Xu, Tianhe; Meng, Xinyue; Wang, Nazi

doi:10.1109/lgrs.2021.3068376

Cited by 8 publications

(2 citation statements)

References 18 publications

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“…In 1993, Martin-Neira initially introduced GNSS-R technology to ocean altimetry [8]. This technology has been successfully verified on various platforms, including ground [9], airborne [10][11][12], and spaceborne [13][14][15]. Compared with the traditional radar altimeters, the GNSS-R altimeter has the advantages of being low-cost and having multiple signal sources and high temporal-spatial resolution [16,17].…”

Section: Introductionmentioning

confidence: 99%

Improving the SSH Retrieval Precision of Spaceborne GNSS-R Based on a New Grid Search Multihidden Layer Neural Network Feature Optimization Method

Wang

Zheng

et al. 2022

Remote Sensing

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The altimetry precision of conventional spaceborne Global Navigation Satellite Systems Reflectometry (GNSS-R) is limited, and the error models are complicated. To compensate for the shortcomings of conventional methods, we present a new grid search multihidden layer neural network feature optimization method (GSMHLFO) for sea surface height (SSH) retrieval. Firstly, the GSMHLFO is constructed by combining the multihidden layer neural network, feature engineering, and a grid search algorithm. Moreover, the retrieval performance of the GSMHLFO and its sensitivity to various features are analyzed. By analyzing 14 feature sets with different information details, we concluded that the elevation, signal-to-noise ratio (SNR), atmospheric delay, and ocean wind speed can provide essential contributions to the SSH retrieval based on GSMHLFO. Secondly, the Technical University of Denmark 18 mean sea surface (DTU18 MSS), which is corrected by the TPXO8 global tide model, was used to verify the GSMHLFO. The number of hidden layers and neurons was optimized using the grid search algorithm. The experimental results show that the proposed GSMHLFO with four hidden layers and 200 neurons per layer has a better retrieval performance. Compared with DTU18, the mean absolute difference (MAD), the root mean square error (RMSE), and the Pearson correlation coefficient (PCC) equal 4.23 m, 5.94 m, and 0.98, respectively. The retrieval precision obtained is significantly improved compared to that reported in the literature for the TDS-1 SSH retrieval. Finally, the retrieval performance of the GSMHLFO and the traditional HALF single-point retracking method were compared. The precision of GSMHLFO is higher than that of traditional retracking method according to MAD, RMSE, and PCC, which are increased by 32.86, 25.00, and 8.99%. The GSMHLFO will provide innovative theoretical and methodological support for the high-precision SSH retrieval of GNSS-R altimetry satellites in the future.

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Section: Introductionmentioning

confidence: 99%

Improving the SSH Retrieval Precision of Spaceborne GNSS-R Based on a New Grid Search Multihidden Layer Neural Network Feature Optimization Method

Wang

Zheng

et al. 2022

Remote Sensing

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show abstract

“…Among them, the height of the earth's reflecting surface relative to the reference ellipsoid can be obtained by measuring the path delay between the direct signal and the reflected signal (Martin-Neira, 1993). Since Martin-Neira first proposed the concept of Passive Reflection and Interference System (PARIS) in 1993, this technology has been verified on various platforms such as ground (Martin-Neira et al, 2001;He et al, 2021), shipborne (Gao et al, 2020), airborne Ruffini et al, 2004;Cardellach et al, 2014), and satellite (Clarizia et al, 2016;Cardellach et al, 2019). Compared with the traditional radar altimeter, GNSS-R altimetry has the advantages of low cost, multi-simultaneous observation, and high spatial coverage.…”

Section: Introductionmentioning

confidence: 99%

Relationship Between Altimetric Quality and Along-Track Spatial Resolution for iGNSS-R Sea Surface Altimetry: Example for the Airborne Experiment

Liu

Zheng

et al. 2021

Front. Earth Sci.

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The altimetric quality and the along-track spatial resolution are the critical parameters to characterize the performance of interferometric global navigation satellite systems reflectometry (iGNSS-R) sea surface altimetry, which is closely related to each other through signal processing time. Among them, the quality of sea surface height (SSH) measurement includes precision and accuracy. In order to obtain higher altimetric quality in the observation area, a longer signal processing time is needed, which will lead to the loss of spatial resolution along the track. In contrast, higher along-track spatial resolution requires more intensive sampling, leading to unsatisfactory altimetric quality. In this study, taking the airborne iGNSS-R observation data as an example, the relationship between the altimetric quality and the along-track spatial resolution is analyzed from the perspectives of precision and accuracy. The results indicate that the reduction in the along-track spatial resolution will improve the altimetric quality. The accuracy range is 0.28–0.73 m, and the precision range is 0.24–0.65 m. However, this change is not linear, and the degree of altimetric quality improvement will decrease as the along-track spatial resolution worsens. The research results in this paper can provide a scientific reference for the configuration of parameters for future spaceborne iGNSS-R altimetry missions.

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Coastal observation of sea surface tide and wave height using opportunity signal from Beidou GEO satellites: analysis and evaluation

Wang

Yang

Zhang

et al. 2022

J Geod

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Coastal Altimetry Using Interferometric Phase From GEO Satellite in Quasi-Zenith Satellite System

Cited by 8 publications

References 18 publications

Improving the SSH Retrieval Precision of Spaceborne GNSS-R Based on a New Grid Search Multihidden Layer Neural Network Feature Optimization Method

Improving the SSH Retrieval Precision of Spaceborne GNSS-R Based on a New Grid Search Multihidden Layer Neural Network Feature Optimization Method

Relationship Between Altimetric Quality and Along-Track Spatial Resolution for iGNSS-R Sea Surface Altimetry: Example for the Airborne Experiment

Coastal observation of sea surface tide and wave height using opportunity signal from Beidou GEO satellites: analysis and evaluation

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